Many text-to-speech applications have only limited ability to adapt to the format of a target. This limitation is more pronounced when applied to the vast differentiation of digitized content available via the World Wide Web. For example, in addition to information pertinent to the user for which the page was accessed, Web pages often contain information that is not relevant, especially if spoken. However, because text-to-speech applications are generally configured to recognize and speak each and every syllable present within the content of the target Web page, the spoken output that results from conversion of these Web pages will contain irrelevant speech and is often garbled, unintelligible, or simply incoherent.
It is therefore advantageous to improve the quality of the spoken content resulting from Web pages and other digitized content accessed via browsing technology, wherein such improvements can be realized in terms of spoken content to the end-user that is meaningful, relevant, and desired. It is likewise advantageous that the spoken content is free from irrelevant information that may be present within the information of the Web pages.